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Nanoscience

Working Paper

Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods

Antti Pihlajamaki, Joonas Hamalainen, Joakim Linja, Paavo Nieminen, Sami Malola, Tommi Karkkainen, Hannu Hakkinen

Version 1 posted 21 February 2020

571

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Theoretical and Computational Chemistry

Working Paper

A Machine Learned Potential for Investigating Single Crystal to Single Crystal Transformations in Complex Organic Molecular Systems

Chengxi Zhao, Honglai Liu, Da-Hui Qu, Andrew Cooper, Linjiang Chen

Version 1 posted 08 October 2024

192

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Theoretical and Computational Chemistry

Working Paper

Capturing the interactions in the BaSnF4 ionic conductor: comparison between a machine-learning potential and a polarizable force field

Xiliang Lian, Mathieu Salanne

Version 2 posted 18 September 2023

348

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Theoretical and Computational Chemistry

Working Paper

Structure and transport properties of LiTFSI-based deep eutectic electrolytes from machine learning interatomic potential simulations

Omid Shayestehpour, Stefan Zahn

Version 1 posted 09 August 2024

721

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Energy

Working Paper

Stereoactive Electron Lone Pairs Facilitate Fluoride Ion Diffusion in Tetragonal-BaSnF4

Xiliang Lian, Damien Dambournet, Mathieu Salanne

Version 1 posted 27 September 2024

83

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Theoretical and Computational Chemistry

Working Paper

From Organic Fragments to Photoswitchable Catalysts: The OFF-ON Structural Repository for Transferable Kernel-based Potentials

Frédéric Célerse, Matthew Wodrich, Sergi Vela, Simone Gallarati, Raimon Fabregat, Veronika Juraskova, Clémence Corminboeuf

Version 1 posted 06 December 2023

107

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Physical Chemistry

Working Paper

Hydrogen Absorption Promoted by Surface Melting: Guidelines for High-Pressure Superhydride Synthesis

Ryuhei Sato, Lewis Conway, Di Zhang, Chris Pickard, Kazuto Akagi, Kartik Sau, Li Hao, Shin-ichi Orimo

Version 3 posted 17 September 2024

322

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Theoretical and Computational Chemistry

Working Paper

Deep Neural Network Potential Demonstrates the Impact of Proton Transfer in CO2 Capture by Liquid Ammonia

Marcos Felipe Calegari Andrade, Sichi Li, Sneha Akhade, Simon Pang

Version 1 posted 07 June 2023

336

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Theoretical and Computational Chemistry

Working Paper

Electrostatic Embedding of Machine Learning Potentials

Kirill Zinovjev

Version 3 posted 07 September 2022

611

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1

Citations

Physical Chemistry

Working Paper

WS22 database: combining Wigner Sampling and geometry interpolation towards configurationally diverse molecular datasets

Max Pinheiro Jr, Shuang Zhang, Pavlo O. Dral, Mario Barbatti

Version 1 posted 19 September 2022

367

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Refine Search

18 results in machine learning potential in Keywords: machine learning potential

Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods

A Machine Learned Potential for Investigating Single Crystal to Single Crystal Transformations in Complex Organic Molecular Systems

Capturing the interactions in the BaSnF4 ionic conductor: comparison between a machine-learning potential and a polarizable force field

Structure and transport properties of LiTFSI-based deep eutectic electrolytes from machine learning interatomic potential simulations

Stereoactive Electron Lone Pairs Facilitate Fluoride Ion Diffusion in Tetragonal-BaSnF4

From Organic Fragments to Photoswitchable Catalysts: The OFF-ON Structural Repository for Transferable Kernel-based Potentials

Hydrogen Absorption Promoted by Surface Melting: Guidelines for High-Pressure Superhydride Synthesis

Deep Neural Network Potential Demonstrates the Impact of Proton Transfer in CO2 Capture by Liquid Ammonia

Electrostatic Embedding of Machine Learning Potentials

WS22 database: combining Wigner Sampling and geometry interpolation towards configurationally diverse molecular datasets

18 results in Keywords: machine learning potential